class_docstr: Test to verify PruningSchedule behavior for step parameters.
  
  This is a parameterized test which runs over all PruningSchedule classes
  to ensure they validate parameters such as begin_step, end_step and frequency
  properly and also apply them correctly during execution.
code: def testFrequencyIsPositive(self, schedule_type):
      with self.assertRaises(ValueError):
          self._construct_pruning_schedule(schedule_type, 10, 1000, 0)
      with self.assertRaises(ValueError):
          self._construct_pruning_schedule(schedule_type, 10, 1000, -1)
      with self.assertRaises(ValueError):
          self._construct_pruning_schedule(schedule_type, 10, 1000, -5)
  
      self._construct_pruning_schedule(schedule_type, 10, 1000, 1)
      self._construct_pruning_schedule(schedule_type, 10, 1000, 10)
  
imports: from absl.testing import parameterized
  import tensorflow
  from tensorflow_model_optimization.python.core.keras import compat
  from tensorflow_model_optimization.python.core.quantization.keras import utils
  from tensorflow_model_optimization.python.core.sparsity.keras import pruning_schedule
label_desc: Use image node_id 5 for calling the PruningScheduleTest obj's underlying member method code with example usage: obj.testFrequencyIsPositive(schedule_type) without return types